Unified Model Research Articles

Distributed adaptive finite-time fault-tolerant cooperative control of heterogeneous multi-agent systems with saturation and disturbances

In this paper, the issue of distributed adaptive finite-time fault-tolerant cooperative control (FT-FTCC) problem is investigated for multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with unknown parameter uncertainties, actuator faults, input saturation and external disturbances. Starting from the dynamic models of the UAVs and UGVs, an unified control model is presented. Then, a sliding-mode estimator is presented to estimate the position of the leader for the followers which only uses the information from neighbours. Next, a distributed adaptive FT-FTCC scheme, which can also deal with the uncertainties, actuator faults, input saturation and disturbances, is proposed by utilising disturbance observers and neural networks. Based on Lyapunov function approach, the tracking errors of all followers subject to the pre-defined desired positions are uniformly ultimately bounded. Finally, simulations are given to validate the efficiency of the developed FT-FTCC scheme.

Anand Model Constants of Sn-Ag-Cu Solders: What Do They Actually Mean?

Abstract Finite element simulations are broadly utilized to calculate the thermally induced mechanical deformations of interconnecting solder materials in electronics. The Anand unified viscoplasticity model is a prevalent choice for simulating the mechanical responses of solder joints, comprising nine parameters whose individual effects are not fully addressed in the literature. For this reason, this study examines the influence of each Anand parameter on the mechanical response of leadless Tin-Silver-Copper solder alloys with varying silver content through comprehensive nonlinear finite element simulations. Anand model coefficients for different SAC alloys, including SAC105, SAC205, SAC305, and SAC405, were sourced from existing literature and used to establish a systematic study matrix for each parameter. These coefficients were then integrated into thermomechanical simulations to induce inelastic deformations in the solder interconnections. The response of the solder interconnects is analyzed using equivalent inelastic strains and inelastic strain energy density. Results indicated that specific Anand parameters could skew the solder joint stress-strain response towards brittle behavior, while other parameters could lead to a more ductile response. Through statistical factorial analysis, the significance of each parameter is found to vary considerably, ranging from negligible to highly significant. The findings of this study are crucial for understanding the behavior of different SAC solder configurations and their expected thermal fatigue performance based on Anand creep constants. Furthermore, this paper provides foundational insights into the interpretation of Anand coefficients and their influence on the mechanical response of solder materials, a topic not yet explored in the existing literature.

Chinese adolescents’ socioeconomic status and English achievement: the mediating role of parental emotional support

Family socioeconomic status (SES) is one of the key indicators of academic achievement, including language achievement. Further investigation of SES’s mechanisms of influence and potential mediators is essential due to the concern regarding the disparities caused by SES in language achievement. This study examines the relation between SES and Chinese adolescents’ English achievement, emphasizing the role of parenting as a conduit for socioeconomic impacts on children and adolescents. The mechanism through which SES influences English achievement was examined in a sample of 1634 junior secondary school students in an urban city in mainland China. A unified model with solid fit indices, comprising both SES and parenting components, was identified through structural equation modeling. As expected, socio-economic disparities appeared to be largely associated with students’ English achievement, and this connection was partially mediated by parental emotional support. Parental emotional support, however, had varied mediating effects that affected the developmental course and shaped achievement outcomes across different SES groups. This study offers valuable insights into the joint contribution of distal SES factors and proximal interactions to achievement outcomes. Intervention efforts and future research implications are discussed.

A Comparative Study of Factors Influencing ADAS Acceptance in Belgium and Vietnam

This paper focuses on the acceptance of ADASs in the traffic safety and human factor domain. More specifically, it examines the predictive validity of the Unified Model of Driver Acceptance (UMDA) for an ADAS bundle that includes forward collision warning, headway monitoring and warning, and lane-keeping assistance in Belgium and Vietnam, two substantially different geographical, socio-cultural, and macroeconomic settings. All systems in the studied ADAS bundle are located at the Society of Automotive Engineer (SAE)-level 0 of automation. We found moderate acceptance towards such an ADAS bundle in both countries, and respondents held rather positive opinions about system-specific characteristics. In terms of predictive validity, the UMDA scored quite well in both countries, though better in Belgium than in Vietnam. Macroeconomic factors and socio-cultural characteristics could explain these differences between the two countries. Policymakers are encouraged to prioritise initiatives that stimulate the purchase and use of the ADAS, rather than on measures meant to influence the underlying decisional balance.

Strong convergence of the empirical spectral distribution of a unified matrix model

Let [Formula: see text] is a positive definite matrix and [Formula: see text] with [Formula: see text] being independent and identically distributed (i.i.d.) centered real random variables. Consider the matrix [Formula: see text] where [Formula: see text] and [Formula: see text] are two projection matrices (deterministic or random) satisfying [Formula: see text] and [Formula: see text]. Additionally, if [Formula: see text] and [Formula: see text] are random matrices, they are independent of [Formula: see text]. In this paper, we demonstrate that the empirical spectral distribution of [Formula: see text] converges almost surely to a non-random distribution when [Formula: see text] and [Formula: see text], assuming [Formula: see text] has finite second moment.

One to All: Towards a Unified Model for Counting Cereal Crop Heads Based on Few-Shot Learning

One to All: Towards a Unified Model for Counting Cereal Crop Heads Based on Few-Shot Learning

A unified LOD model for river network and DEM based on an improved 3D_DP algorithm

The level of detail (LOD) modelling of vector and terrain data is individual, resulting in geometric and topological inconsistencies in simplification processes. The three dimension Douglas Peucker (3D_DP)algorithm can realize gradual discrete point selection through threshold, which is mainly used in DEM synthesis, and its simplified process is very suitable for the dynamic establishment of massive data sets. A new LOD modeling method based on 3D_DP algorithm is proposed to simplify the consistency of river network vector elements and DEM in this paper. The specific steps are as follows: Firstly, the “Bending Adjustment Index (BAI)” is introduced to improve the 3D_DP algorithm, called the improved 3D_DP algorithm; Secondly, the DEM data is extracted into a 3D discrete point dataset, and the river line vector data is also converted into a discrete point dataset, assigned with elevation attributes, and merges with the DEM’s 3D discrete points. The merged point datasets are equenced based on the importance of each point, which are computed by the improved 3D_DP algorithm. The order of deleting points is determined by the sequence and the corresponding model spatial errors are calculated with the deletion of points. Then, the DEM’s 3D discrete points are constructed a Delaunay network with the river line as a mandatory constraint condition. The required triangulation is called in real time with the change of sight distance depending on the simple correspondence between screen projection error and model space error, and the unified LOD model for river line vector and DEM is established. The results show that the river’s overall shape and the terrain’s main features can be reserved under the same simplified factor based on the improved 3D_DP algorithm. The unified LOD model for the river network and DEM is feasible under the importance sequence of merged point datasets by the improved 3D_DP algorithm. Under the proper operation of data blocking, the rendering frame rate can meet practical application requirements.

The cohesin complex: structure and principles of interaction with dna

Accurate duplication and separation of long linear genomic DNA molecules is associated with a number of purely mechanical problems. SMC complexes are key components of the cellular machinery that ensures decatenation of sister chromosomes and compaction of genomic DNA during division. Cohesin, one of the essential eukaryotic SMC complexes, has a typical ring structure with intersubunit pore through which DNA molecules can be threaded. The capacity of cohesin for such topological entrapment of DNA is crucial for the phenomenon of post-replicative association of sister chromatids better known as cohesion. Recently, it became apparent that cohesin and other SMC complexes are in fact motor proteins with a very peculiar movement pattern leading to the formation of DNA loops. This specific process was called loop extrusion. Extrusion underlies multiple cohesin’s functions beyond cohesion, but the molecular mechanism of the process remains a mystery. In this review, we have summarized data on the molecular architecture of cohesin, the influence of ATP hydrolysis cycle on this architecture, and the known modes of cohesin–DNA interactions. Many of the seemingly disparate facts presented here will probably be incorporated in a unified mechanistic model of loop extrusion in a not so far future.

Unifying Model Execution and Deductive Verification with Interaction Trees in Isabelle/HOL

Model execution allows us to prototype and analyse software engineering models by stepping through their possible behaviours, using techniques like animation and simulation. On the other hand, deductive verification allows us to construct formal proofs demonstrating satisfaction of certain critical properties in support of high-assurance software engineering. To ensure coherent results between execution and proof, we need unifying semantics and automation. In this paper, we mechanise Interaction Trees (ITrees) in Isabelle/HOL to produce an execution and verification framework. ITrees are coinductive structures that allow us to encode infinite labelled transition systems, yet they are inherently executable. We use ITrees to create verification tools for stateful imperative programs, concurrent programs with message passing in the form of the CSP and Circus languages, and abstract system models in the style of the Z and B methods. We demonstrate how ITrees can account for diverse semantic presentations, such as structural operational semantics, a relational program model, and CSP's failures-divergences trace model. Finally, we demonstrate how ITrees can be executed using the Isabelle code generator to support the animation of models.

A comprehensive study of beam modal functions in the free vibration analysis of cylindrical shells: Critical examination on the applicability to the clamped-free boundary condition

Over the past few decades, approximate methods that can provide solutions of sufficient accuracy have received considerable attention in the free vibration analysis of cylindrical shells, where a great deal of studies adopted the beam modal functions as the trial functions for the axial mode shapes of cylindrical shells. Nevertheless, most studies were restricted to the application of single term beam modal function and failed to simulate elastic boundary conditions of cylindrical shells, while the accuracy of the corresponding methods has recently sparked significant controversy, especially for cylindrical shells under the clamped-free boundary condition. This paper presents a comparative study of three forms of beam modal functions in the free vibration analysis of cylindrical shells, one of which is proposed for the first time to simulate elastic boundary conditions of cylindrical shells. A unified model is developed using the general Rayleigh–Ritz method, incorporating the breathing modes with circumferential orders being zero, and four types of commonly used thin shell theories, namely the Donnell, Reissner, Love, and Sanders theories. From both perspectives of natural frequencies and mode shapes, numerical results are validated by comparison with those existing in the literature and those calculated from the finite element method (FEM). The results not only clarify the distinction of different forms of beam modal functions used in the Rayleigh-Ritz method, but also provide explanations for the controversy raised in recent studies. Furthermore, the unified formulations can be extended to vibration analysis of various forms of shell structures, and can also be helpful to the vibration analysis of beams and plates with elastic boundary conditions.

Enhancing Medical Image Classification with Unified Model Agnostic Computation and Explainable AI

Background: Advances in medical image classification have recently benefited from general augmentation techniques. However, these methods often fall short in performance and interpretability. Objective: This paper applies the Unified Model Agnostic Computation (UMAC) framework specifically to the medical domain to demonstrate its utility in this critical area. Methods: UMAC is a model-agnostic methodology designed to develop machine learning approaches that integrate seamlessly with various paradigms, including self-supervised, semi-supervised, and supervised learning. By unifying and standardizing computational models and algorithms, UMAC ensures adaptability across different data types and computational environments while incorporating state-of-the-art methodologies. In this study, we integrate UMAC as a plug-and-play module within convolutional neural networks (CNNs) and Transformer architectures, enabling the generation of high-quality representations even with minimal data. Results: Our experiments across nine diverse 2D medical image datasets show that UMAC consistently outperforms traditional data augmentation methods, achieving a 1.89% improvement in classification accuracy. Conclusion: Additionally, by incorporating explainable AI (XAI) techniques, we enhance model transparency and reliability in decision-making. This study highlights UMAC’s potential as a powerful tool for improving both the performance and interpretability of medical image classification models.

The impact of preceding convection on the development of Medicane Ianos and the sensitivity to sea surface temperature

Abstract. Medicane Ianos in September 2020 was one of the strongest medicanes observed in the last 25 years. It was, like other medicanes, a very intense cyclone evolving from a baroclinic mid-latitude low into a tropical-like cyclone with an axisymmetric warm core. The dynamical elements necessary to improve the predictability of Ianos are explored with the use of simulations with the Met Office Unified Model (MetUM) at 2.2 km grid spacing for five different initialisation times, from 4 to 2 d before Ianos's landfall. Simulations are also performed with the sea surface temperature (SST) uniformly increased and decreased by 2 K from analysis to explore the impact of enhanced and reduced sea surface fluxes on Ianos's evolution. All the simulations with +2 K SST are able to simulate Medicane Ianos, albeit too intensely. The simulations with control SST initialised at the two earliest times fail to capture intense preceding precipitation events at the right locations and the subsequent development of Ianos. Amongst the simulations with −2 K SST, only the one initialised at the latest time develops the medicane. Links between sea surface fluxes and upper-level baroclinic processes are investigated. We find three elements that are important for Ianos's development. First, an area of low-valued potential vorticity (PV), termed a “low-PV bubble”, formed within a trough above where Ianos developed; diabatic heating associated with a preceding precipitation event triggered a balanced divergent flow in the upper levels, which contributed to the creation and maintenance of this low-PV bubble as shown by results from a semi-geostrophic inversion tool. Second, a quasi-geostrophic ascent was forced by middle and upper levels during Ianos's cyclogenesis. It is partially associated with the geostrophic vorticity advection, which is enhanced by the growth and advection of the low-PV bubble. Third, diabatic heating dominated by deep convection formed a vertical PV tower during Ianos's intensification and continued to produce diabatically induced divergent outflow aloft, thus sustaining Ianos’s development. Simulations missing any of these three elements do not develop Medicane Ianos. Our results imply the novel finding that preceding convection was essential for the subsequent development of Ianos, highlighting the importance of the interactions between near-surface small-scale diabatic processes and the upper-level quasi-geostrophic flow. A warmer SST strengthens the processes and thus enables Ianos to be predicted in simulations initiated at the earlier times.

A Unified Model for Chinese Cyber Threat Intelligence Flat Entity and Nested Entity Recognition

In recent years, as cybersecurity threats have become increasingly severe and cyberattacks have occurred frequently, higher requirements have been put forward for cybersecurity protection. Therefore, the Named Entity Recognition (NER) technique, which is the cornerstone of Cyber Threat Intelligence (CTI) analysis, is particularly important. However, most existing NER studies are limited to recognizing single-layer flat entities, ignoring the possible nested entities in CTI. On the other hand, most of the existing studies focus on English CTIs, and the existing models performed poorly in a limited number of Chinese CTI studies. Given the above challenges, we propose in this paper a novel unified model, RBTG, which aims to identify flat and nested entities in Chinese CTI effectively. To overcome the difficult boundary recognition problem and the direction-dependent and distance-dependent properties in Chinese CTI NER, we use Global Pointer as the decoder and TENER as the encoder layer, respectively. Specifically, the Global Pointer layer solves the problem of the insensitivity of general NER methods to entity boundaries by utilizing the relative position information and the multiplicative attention mechanism. The TENER layer adapts to the Chinese CTI NER task by introducing an attention mechanism with direction awareness and distance awareness. Meanwhile, to cope with the complex feature capture of hierarchical structure and dependencies among Chinese CTI nested entities, the TENER layer solves the problem by following the structure of multiple self-attention layers and feed-forward network layers superimposed on each other in the Transformer. In addition, to fill the gap in the Chinese CTI nested entity dataset, we further apply the Large Language Modeling (LLM) technique and domain knowledge to construct a high-quality Chinese CTI nested entity dataset, CDTinee, which consists of six entity types selected from STIX, including nearly 4000 entity types extracted from more than 3000 threatening sentences. In the experimental session, we conduct extensive experiments on multiple datasets, and the results show that the proposed model RBTG outperforms the baseline model in both flat NER and nested NER.

NFT-Based Framework for Digital Twin Management in Aviation Component Lifecycle Tracking

The paper presents a novel framework for implementing decentralized algorithms based on non-fungible tokens (NFTs) for digital twin management in aviation, with a focus on component lifecycle tracking. The proposed approach uses NFTs to create unique, immutable digital representations of physical aviation components capturing real-time records of a component’s entire lifecycle, from manufacture to retirement. This paper outlines detailed workflows for key processes, including part tracking, maintenance records, certification and compliance, supply chain management, flight logs, ownership and leasing, technical documentation, and quality assurance. This paper introduces a class of algorithms designed to manage the complex relationships between physical components, their digital twins, and associated NFTs. A unified model is presented to demonstrate how NFTs are created and updated across various stages of a component’s lifecycle, ensuring data integrity, regulatory compliance, and operational efficiency. This paper also discusses the architecture of the proposed system, exploring the relationships between data sources, digital twins, blockchain, NFTs, and other critical components. It further examines the main challenges of the NFT-based approach and outlines future research directions.

New methods and applications of structural dynamics modeling for railway freight liquid tank

As railway freight technology advances towards heavy-load, high-speed capabilities, the design of liquid tank products is evolving to prioritize high load capacity, lightweight, high-strength materials, low structural rigidity, and thin-walled construction. These changes result in pronounced nonlinear low-frequency vibrations during rail operation. Addressing these complex liquid-solid coupled vibrations requires accurate dynamic modeling of the structural system. This paper introduces a novel dynamic modeling method for liquid tank products based on acousto-elastic coupling. This approach considers the swaying of the free liquid surface and liquid-solid interactions, enabling precise characterization of these dynamics in a unified model. Specifically, it tackles the challenge of uneven node swaying forces caused by non-uniform liquid surface meshing, presenting a technique and program to adjust swaying recovery forces based on nodes’ actual coverage area. This method’s liquid sway frequency calculations showed a 10% precision increase over traditional methods, more accurately reflecting liquid vibration states. The paper applies these techniques to a single tank container and an LNG tank container on a flatbed trailer. Through theoretical, simulation, and experimental comparisons, the model’s accuracy and reasonableness were validated. This low-dimensionality, high-precision dynamic model is universally applicable, especially valuable in modeling complex engineering structures.

Retriever: A view-based approach to reverse engineering software architecture models

Software systems, which have become an integral part of our daily lives, are constantly evolving and growing in complexity. The challenge of understanding and managing these systems has led to a shift towards automated extraction of models from software artifacts. However, extracting architectural models for web service or microservice systems is challenging due to the heterogeneity of formats, languages, and semantics. This challenge arises from the independent deployment and loose coupling of services, as well as the diverse technologies and platforms that comprise the heterogeneous artifacts. This paper addresses this issue with two key ideas: a knowledge representation model for diverse artifacts and a framework for integrating individual views into a unified architectural model. The former involves model-to-model transformations that consider technology-specific relationships and concepts. At the same time, the latter uses model transformation and composition techniques to create a unified model based on an existing metamodel. This work goes beyond the current state of the art by introducing an approach for reconstructing component-based software architectures and combining model-driven reverse engineering processes to capture information across multiple views. As empirical evidence of its applicability and accuracy, we report on its successful application in real projects of different sizes. Our evaluation shows scalability in generating architectural models and can reconstruct the components of a software system and their interactions with F1 values up to 0.94 for structural properties and up to 0.88 for behavioral properties.

Buffeting performance of long-span bridges with different span affected by parametric typhoon wind

Currently, typhoon-related performance of long span bridges usually focus on a specific wind record such as wind speed and turbulence intensity during a full typhoon, however, the inter-correlation among wind characteristic parameters under typhoon wind climate is ignored. The existing investigation about structural responses during typhoon attacks are still limited at case-study analysis, and hardly provide a generalized framework to evaluate the structural performance especially for typhoon landing whole process. This study utilizes the measured wind speeds of the strong typhoon "Hagupit" to establish a unified typhoon parametric model, during which the correlation of typhoon wind parameters including angle of attack (AoA), turbulence intensity, integral length scale and mean wind speed were taken into consideration. The measured typhoon process charactered with center-through effect with M-type average wind speed curve. Furthermore, the structural performance of long-span bridges with different spans from 1500 m to 2500 m main span was systematically studied. The aerodynamic parameters of the bridge deck section, including the aerostatic coefficients, flutter derivatives at different AoAs, and aerodynamic admittance under different oncoming flow conditions were identified through wind tunnel tests. Finally, the wind-induced buffeting performance was calculated by the buffeting frequency domain algorithm, showing various structural wind effect characteristics during the typhoon landing whole process. The maximal buffeting response is not necessarily related with the wind speed, and other wind characteristics especially turbulence intensity and AoA, etc. also affect on the results.

Uniaxial compressive behavior and unified damage constritutive model of various types of recycled coarse aggregate concrete under freeze-thaw action

Uniaxial compressive behavior and unified damage constritutive model of various types of recycled coarse aggregate concrete under freeze-thaw action

Effect of initial temperature damage on the static and fatigue performance of all-lightweight shale ceramsite concrete

The effects of initial temperature damage on the static and compressive fatigue properties of LC30 all-lightweight shale ceramsite concrete (ALWSCC) were studied. The curing conditions ranged from -5 °C to -30 °C without antifreeze, with an elevated temperature range of 100 °C to 400 °C applied after 28 days of standard curing. We tested the static strength, elastic modulus, and stressstrain curves of ALWSCC, as well as its uniaxial compression fatigue life and ƐN curves under different stress levels. The credibility of data from only three test samples per condition was statistically analyzed, and we explored how temperature, aggregate properties, and concrete pore structure affect performance. The results indicate that the impact of temperature on the static and fatigue performance of ALWSCC can be described by a unified damage model. The Hillerborg characteristic length effectively captures the brittleness induced by temperature changes. Using the two-parameter Weibull equation and various fatigue equations that account for failure probability and temperature, the fatigue life predictions were accurate. Although low and high temperatures affect ALWSCC differently, temperature effects combined with static and fatigue loads further accelerate its deterioration.

A Unified Novel Koopman-Based Model Predictive Control Scheme to Achieve Seamless Stabilization of Nonlinear Dynamic Transitions in Inverter-Based Stochastic Microgrid Clusters

A Unified Novel Koopman-Based Model Predictive Control Scheme to Achieve Seamless Stabilization of Nonlinear Dynamic Transitions in Inverter-Based Stochastic Microgrid Clusters